ORIGINAL RESEARCH

Molecular docking studies on analogues of quercetin withD-alanine:D-alanine ligase of Helicobacter pylori

Salam Pradeep Singh • Rocktotpal Konwarh •

Bolin Kumar Konwar • Niranjan Karak

Received: 5 March 2012 / Accepted: 17 August 2012

� Springer Science+Business Media, LLC 2012

Abstract Helicobacter pylori (Hp) is a human pathogen

associated with myriad of diseases such as gastritis, peptic

ulceration, piles and gastric cancer. The resistance of Hp

against antimicrobial agents has increased just as that of

other pathogens worldwide, thus emphasizing an urgent

need for developing new antibacterial agents. The D-ala-

nine:D-alanine ligase (Ddl, EC 6.3.2.4) has been considered

as a putative antimicrobial drug target and a lot of inhibitor

screening efforts have been made. Quercetin, a member of

the flavonoids, characterized by a flavone nucleus com-

posed of two benzene rings linked through a heterocyclic

pyrone ring is reported to possess antibacterial activity

against H. pylori Ddl (HpDdl) enzyme. In this milieu, we

have performed molecular docking analysis of quercetin

and its analogues at the active site of HpDdl. Some of the

screened compounds showed better affinity and interaction

with HpDdl enzyme. The docking analysis and absorption,

distribution, metabolism and toxicity study forward few of

them as plausible lead molecule or a novel class of drugs

with enhanced pharmacological properties.

Keywords Antimicrobial agent � Antibacterial activity �Flavonoids � Molecular docking

Introduction

The elucidation of the link between Helicobacter pylori

(Hp) and gastritis as well as ulceration of the stomach

fetched J. Robin Warren and Barry J. Marshall the Nobel

Prize in Medicine for the year 2005 (Sood, 2006). Since the

discovery of the bacterium, the exact etiopathogenesis is

continuously being updated. A perusal of recent reports

unmasks the association of the bacterium with diverse

extra-digestive morbidity, including insulin resistance

syndrome (Polyzos et al., 2011) and numerous auto-

immune disorders (Hasni et al., 2011) apart from adeno-

carcinoma and gastric lymphoma. Furthermore, the oral

cavity has also been proposed as a reservoir of Hp infection

(Abdel-Monem et al., 2011). The risk intensifies as it has

been hypothesized that the incidence of primary open-

angle glaucoma may increase due to industrialization via

quick transmission of Hp infection (Zavos et al., 2011).

The gamut of enzymes catalyzing the synthesis of the

peptidoglycan framework of the cell wall is a well-

corroborated target for the antibacterial therapy (Wu et al.,

2008a, b). D-alanine:D-alanine ligase (Ddl) synthesizes the

terminal dipeptide, D-Ala:D-Ala, of the peptidoglycan

precursor UDPMurNAc-pentapetide, a crucial building

block involved in peptidoglycan cross-linking. Ala ana-

logues (Neuhaus and Hammes, 1982), transition state

analogues (Ellsworth et al., 1996) and allosteric inhibitor

(Liu et al., 2006) are the reported inhibitors of Ddl.

Recently, HpDdl has been identified as a new target for

quercetin (3,30,40,5,7-pentahydroxyflavone) (Wu et al.,

2008a). It is pertinent to mention that HpDdl keeps two

conservatively substituted residues (Ile16 and Leu241) and

two non-conserved residues (Leu308 and Tyr311) in

the active region (that might partly contribute to the

unique catalytic properties of the enzyme). Furthermore, a

S. P. Singh (&) � B. K. Konwar

Bioinformatics Infrastructure Facility, Department of Molecular

Biology and Biotechnology, Tezpur University,

Tezpur 784028, Assam, India

e-mail: salampradeep@gmail.com

R. Konwarh � N. Karak (&)

Advanced Polymer and Nanomaterial Laboratory,

Department of Chemical Sciences, Tezpur University,

Tezpur 784028, Assam, India

e-mail: nkarak@tezu.ernet.in

123

Med Chem Res

DOI 10.1007/s00044-012-0207-7

MEDICINALCHEMISTRYRESEARCH

310-helix (including residues from Gly306 to Leu312) near

the D-Ala binding region may be involved in D-Ala binding

and conformational change of the enzyme (Wu et al.,

2008b).

Quercetin is a member of the flavonoids, characterized

by a flavone nucleus composed of two benzene rings linked

through a heterocyclic pyrone ring. It mainly occurs in

apples, onions, tea, red wines and berries that show anti-

bacterial action by acting on multiple cellular targets

(Cushnie and Lamb, 2011). Enzymatic assay against

HpDdl established quercetin as the reversible inhibitor,

competitive with one substrate ATP and non-competitive

with the other substrate D-Ala (Wu et al., 2008a). This was

indicative of probable overlap of the binding site of quer-

cetin with the active centre, especially the binding grove of

ATP but not that of D-Ala. However, it showed poorer anti-

Hp activity in comparison to apigenin. This may be due to

greater hydrophilic nature of quercetin in comparison to

apigenin, resulting in its poorer penetration into the bac-

terial cell (Ohemeng et al., 1993). It is pertinent to mention

that flavonoids also target the cytoplasmic membrane

(Mirzoeva et al., 1997) and the hydrophobicity might

facilitate their interactions with the membrane. Further-

more, clinical use of quercetin is limited by its low oral

bioavailability. This necessitates the molecular modifica-

tion of quercetin to enhance its pharmacological properties.

Thus, probing into the binding of quercetin and its

analogues to the HpDdl is an interesting proposition in the

framework of structure-based drug discovery. In this con-

text, in silico ligand–protein docking study could be

instrumental in comprehending and predicting molecular

recognition, explication of the binding modes and pre-

dicting binding affinity (Morris and Lim-Wilby, 2008).

Furthermore, it has been estimated that nearly 50 % of

drugs fail because of unacceptable efficacy, which includes

poor bioavailability as a result of ineffective intestinal

absorption and undesirable metabolic stability (Kennedy,

1997). It has also been estimated that up to 40 % of drug

candidates have failed in the past because of safety issues

(DiMasi, 1995). In view of this aspect, we have also carried

out ADME–toxicity (ADME–Tox) prediction (absorption,

distribution, metabolism and toxicity) of quercetin and its

analogues used in our study to evaluate the properties

crucial to the final clinical success of a drug candidate.

Experimental

Protein preparation

The three-dimensional crystal structure of Ddl from Hp

(Wu et al., 2008a, b) (PDB ID: 2PVP) determined by X-ray

crystallography was retrieved from the Protein Databank

Bank (http://www.rcsb.org/) was imported in the Molegro

Virtual Docker (MVD) (Molegro APS). The coordinates of

the dimeric crystallographic structure of Ddl is complexed

with water molecules. Considering that the monomers are

identical and independent of each other, only monomer A

from the enzyme, we selected to perform our molecular

docking studies. This procedure reduced the computation

time by half. Also, the co-crystallized water molecules

were removed from both the monomers using the software

Molegro Virtual Docker (MVD�) (Molegro APS; Thomsen

and Christensen, 2006).

Compound retrieval and chemical similarity search

The 2D structure of quercetin (CID5280343) was retrieved

from the NCBI PubChem database (Bolton et al., 2008;

Wang et al., 2010). In addition, we performed a chemical

structure search of quercetin in the NCBI PubChem data-

base (Bolton et al., 2008; Wang et al., 2010) to retrieve the

related compound and analogues. The search parameters

were set at 95 % similarity subjected to Lipinski rule of

five filters (Lipinski, 2000; Lipinski et al., 1997).

The 2D structure of quercetin (CID5280343) and the

compounds retrieved from the PubChem compound search

at 95 % similarity (Bolton et al., 2008; Wang et al., 2010)

were converted to their corresponding three-dimensional

structures using the ChemOffice (2010) (CambridgeSoft

Corporation 2010) for our docking purposes. The energy of

these compounds were optimized using MM2 force field

methods (Burkert and Allinger, 1982) and saved as SYBL

mol2 files using ChemOffice (2010) (CambridgeSoft

Corporation 2010).

Computation

For docking purposes, the active site residues (Leu308 and

Tyr311), responsible for the distinctive enzymatic activity

(Wu et al., 2008b) were set as the search space. The active

site residues of search space were set inside a restriction

sphere of radius 13 A (X 6.05, Y -16.68, Z 22.58) using

MVD� (Molegro APS).

Bond flexibility of the compounds was set along with

the side chain flexibility of the protein for search space

(Leu308 and Tyr311), set with a tolerance of 1.10 and

strength of 0.90 for docking simulations. RMSD threshold

for multiple cluster poses was set at 2.00 A (Yadava et al.,

2011). The docking algorithm was set at a maximum

iteration of 1,500 with a simplex evolution size of 50 and a

minimum of 10 runs were performed for each compound.

The best pose of each compound was selected for the

subsequent ligand–protein interaction energy analysis.

Molecular docking was carried out using Molegro Virtual

Docker (Molegro APS). MVD is molecular visualization

Med Chem Res

123

and molecular docking software based on a differential

evolution algorithm; the solution of the algorithm takes into

account the sum of the intermolecular interaction energy

between the ligand and the protein and the intramolecular

interaction energy of the ligand. The docking energy scoring

function is based on the modified piecewise linear potential

(PLP) with new hydrogen bonding and electrostatic terms

included. Full description of the algorithm and its reliability

as compared to other common docking algorithm can be

found in literature (Thomsen and Christensen, 2006).

Enzymatic inhibition and antibacterial assay conducted

by Wu et al. (2008a)

The authors would like to highlight the reported (Wu et al.,

2008a) fact that quercetin exhibited 50 % lower inhibitory

concentration (IC50) (Table 1) and inhibitor binding con-

stant (Ki) values than apigenin against both the HpDdl and

Escherichia coli DdlB. The inhibitor binding constant, Ki

values were found to be 4.3 and 31.0 lM, respectively, for

quercetin and apigenin, competitive for ATP. The two

additional hydroxyls on the flavone skeleton of quercetin in

structure might facilitate its inhibitory activity and binding

affinity to Ddl. However, Wu et al. (2008a) have proposed

that the differential hydrophilicity (and consequently dif-

ference in penetration potency into the bacterial cell wall)

of quercetin and apigenin may be ascribed for the former’s

poorer anti-Hp activity in comparison to the moderate MIC

(25 lg mL-1) of the latter (Table 2). These necessitate the

molecular modification of quercetin to enhance its phar-

macological properties. Thus, these inhibition study data

dictated our decision to restrict the screening of quercetin

alone and the analogues.

ADME–Tox prediction

In addition, ADME–Tox predictions for the top docking

hits were calculated using ACD/I-Lab 2.0 (Advanced

Chemistry Development, Inc.). ACD/I-Lab 2.0 is a web-

based service that provides instant access to spectral and

chemical databases, and predicts properties including

physicochemical, ADME, toxicity characteristics. The

LD50 mouse (intraperitoneal, oral, intravenous, subcuta-

neous) and probability of health effect of blood, cardio-

vascular system, gastrointestinal system, kidney, liver and

lung were predicted for the top docking hits and compar-

ative analysis were performed.

Results and discussion

Quercetin (3,30,40,5,7-pentahydroxyflavone) is an ubiqui-

tously distributed polyphenolic flavonoid of the plant

kingdom, present as a secondary metabolite (Murakami

et al., 2008). It is pertinent to mention that flavonoids

contain a basic skeleton of diphenylpropane (C6–C3–C6).

Quercetin is commonly found as O-glycosides in which at

least one hydroxyl group is substituted by various types of

sugars. Hydroxyl groups at the 30 and 40-positions in the

B-ring (the so-called catechol group) and the 3-position in

the C-ring are responsible for a number of bioactivities

(including the free radical scavenging of DPPH) of quer-

cetin. In this report, we have highlighted the inhibition of

HpDdl by quercetin and its analogues.

Molecular docking was carried out and the top poses

docked at the active site region of the protein are shown in

Table 3. In post-docking analysis, it is observed that

compounds ID 9818879, 6477685, 21633676, 25202270,

6477683, 25202413 and 10636768 have higher rerank

score (in terms of negative energy) than quercetin and

compound ID 10359384, 44258703 have lesser rerank

score than quercetin as shown in Table 3. The rerank score

is a linear combination of E-inter (steric, van der Waals,

hydrogen bonding, electrostatic) between the ligand and

the protein, and E-intra (torsion, sp2–sp2, hydrogen bond-

ing, van der Waals, electrostatic) of the ligand weighted by

pre-defined coefficients (Thomsen and Christensen, 2006).

We have also carried out a detailed analysis of the top

poses in terms of ligand–protein interaction energy. The

ligand–protein interaction energy analysis (both electro-

static and H-bond energy) was calculated in order to get a

better understanding of the variations between the binding

mode of each compound and the molecular factors

responsible for the activity.

Table 1 Enzymatic inhibition of quercetin against Helicobacterpylori D-alanine:D-alanine ligase (HpDdl) and Escherichia coli DdlB

(EcDdlB) (Wu et al., 2008a)

Enzyme Inhibitor IC50 (lM)

HpDdl Quercetin 48.5 ± 4.3

Apigenin 132.7 ± 14.4

EcDdlB Quercetin 19.9 ± 1.8

Apigenin 163.0 ± 26.2

Table 2 Minimum inhibitory concentrations (MICs) of quercetin

against H. pylori and E. coli (Wu et al., 2008a)

Compound MIC (lg mL-1)

H. pylori strain E. coli strain

SS1 43504 JM109 25922

Quercetin 200 100 300 300

Apigenin 25 25 200 [200

Med Chem Res

123

Table 3 Molecular docking poses score for the top ten docking hits

S. no. Compound ID Residue Interaction

energy

(kcal mol-1)a

Interaction

dist. (A)

H-bond

energy

(kcal mol-1)b

MolDock

scorecRerank

scored

1 9818879

O

O

O

O

O

O

O

H

H

H

H

H

H

H

H

H

H

H

H

H

H

Arg286 -2.42 2.82 -15.65 -100.64 -82.13

Arg286 -1.87 3.09

His96 -0.59 2.89

Glu101 -2.5 2.66

Ile304 -1.52 2.48

Ser307 -2.5 2.69

Gly306 -2.5 2.63

Tyr311 -0.37 2.34

2 6477685

O

O O

O

O

O

H

H

H

HH

HH

H

H H

H

H Glu13 -2.5 3.1 -21.93 -92.79 -77.86

Glu101 -2.5 3.01

Ser177 -0.48 3.45

Glu233 -1.18 3.19

Glu233 -2.5 3.1

Glu233 -2.49 3.1

Arg286 -1.46 3.13

Arg286 -2.5 2.6

Ile304 -1.32 2.99

Tyr311 -2.5 2.83

Tyr311 -2.5 3.03

3 21633676

O

O

O

O

O

O

O

H

HH

HH

H

H

H

H

H

HH Gly306 -1.10 3.24 -13.19 -78.9 -75.25

Ser177 -1.03 3.39

Asn302 -2.5 2.63

Ser177 -0.62 3.43

Glu101 -2.5 2.84

His96 -1.28 2.79

Glu101 -2.5 2.73

Ile304 0.08 2.29

Tyr311 -2.31 3.14

4 25202270

O

O

OO

O

O

-O

H

H

H

H

H

HH

H

H

H

H Arg286 -2.5 2.85 -10.09 -83.32 -72.68

Gly306 -1.35 3.30

Glu233 -2.5 2.69

Tyr311 -2.5 3.06

Glu101 -2.5 2.95

Ile304 -1.25 2.45

Med Chem Res

123

Table 3 continued

S. no. Compound ID Residue Interaction

energy

(kcal mol-1)a

Interaction

dist. (A)

H-bond

energy

(kcal mol-1)b

MolDock

scorecRerank

scored

5 6477683

O

O

O

O

O

H

H

H

H

H

H

HH

H

H

H

H Arg286 -2.07 3.1 -18.67 -83.18 -72.39

Arg286 -2.47 2.93

Glu13 -2.5 3.1

His96 -0.6 3.48

Glu233 -1.04 3.14

Glu233 -2.5 3.01

Tyr311 -2.5 2.82

Glu233 -2.5 3.1

Tyr311 -2.5 2.71

6 25202413

O

O

O

O

-O

O

O

H

H

H

H

H

H

H

H

H

HH Gly306 -0.83 3.26 -9.66 -77.19 -70.35

Ser177 -1.48 3.3

Asn302 -2.5 2.62

Tyr311 -0.83 2.4

Ser177 -0.35 3.48

His96 -1.37 3.06

Glu101 -2.49 2.6

Ile304 -1.25 2.45

7 10636768O

O

O O

O

HH

H

H

H

H

H

H

H

H

H

H

Arg286 -0.31 3.05 -8.32 -82.89 -70.27

Tyr311 -2.5 2.61

Asn302 0.46 2.25

Ser307 -1.89 3.22

Glu101 -1.21 3.18

Glu101 -2.45 3.1

Asn302 -0.39 3.52

8 Quercetin

O

O

OO

O

O

OH

H

H

H

H

H

H

H

H

H

Arg286 -0.59 2.85 -12.11 -78.31 -70.1

Arg286 -0.82 2.75

Asn302 -1.82 2.76

Arg286 -2.41 2.81

Arg286 -1.82 3.11

His96 -0.55 2.95

Glu101 -2.5 2.62

Ile304 -1.6 2.49

9 10359384

O

O

O

O

O

O O

O

HH

H

H

H

H

H

H

H

H

HH Arg286 -0.94 3.41 -14.88 -75.13 -69.23

Gly306 -1.3 3.3

Ser177 -1.02 3.4

Asn302 -1.62 2.5

Tyr311 -2.41 3.12

Glu233 -2.5 2.7

Tyr311 4.79 1.75

His96 -1.11 2.95

Glu101 -2.49 3.10

Ile304 0.29 2.27

Med Chem Res

123

Table 3 also enlists the ligand–protein interaction

energy calculation including the residues present, their

interaction distances and interaction energy. The top poses

were found to be docked into the active site of the search

space exhibiting both bonded and non-bonded interaction.

The top three docking hits CID9818879, CID6477685 and

CID21633676 having higher rerank score showed common

molecular interaction with Glu101, Ile304, Tyr311 resi-

dues. Moreover, the interaction with the non-conserved

residues in the active site residue Tyr311 was found to be

dominating in the top ten docking hits. Here only the

docking poses have been shown for the top three com-

pounds (CID9818879, CID6477685 and CID21633676)

and quercetin in Figs. 1a–c, 2a–c, 3a–c and 4a–c. The

snapshots show the variation in the conformational modes

of the molecules under consideration. The authors would

like to highlight a pertinent issue at this juncture. Natural

products like quercetin are capable of binding to multiple

targets primarily due to their mode of generation as pro-

posed by Ji et al. (2009). During the eventual steps in the

biosynthesis of the quercetin molecule, different syntheta-

ses with diverse architecture and molecule binding cavities

are involved. The differential target binding modes of the

quercetin molecule seems to be preconditioned by the

varied interactions with the enzyme moieties during the

former’s biosynthesis. The inhibition of phosophatidyli-

nositol-3-kinase (with kinase-like fold), 3-hydroxyisobu-

tyryl-CoA hydrolase (with ClpP/crotonase fold) and helix-

turn-helix type transcriptional regulator (with tetracycline

repressor-like fold) by quercetin marshals in support of this

fact. Core structure of quercetin seems to inherit a spec-

trum of binding groups and certain level of flexibility that

facilitates its interaction with a plethora of unintended

proteins with similar ligand binding cavities.

The binding of these compounds at the active site region

reveals the binding affinity of these compounds is better

than quercetin. Furthermore, we have calculated the cor-

relation between molecular weight and the hydrogen

bonding energy for the top docking hits resulting in a very

low correlation value of -0.23 indicating that the predicted

hydrogen bonding energy was mainly due to specificity and

not due to molecular size.

It is pertinent to mention that in vitro and in vivo experi-

ments often lay the foundation stone and complements/

confirms computational and docking analyses. In this milieu,

as noted previously, Wu et al. (2008b) have kinetically and

structurally characterized the Ddl of Hp strain SS1 (HpDdl).

The documented apparent Km of ATP (0.87 lM), Km1

(1.89 mM) and Km2 of D-Ala (627 mM), and kcat

(115 min-1) at pH 8.0 vouched for its relatively weak

binding affinity and poor catalytic activity against the sub-

strate D-Ala in vitro. Although, HpDdl from Hp has been

shown to exhibit low catalytic efficiency in vitro, it still

retained its function as Ddl in vivo. By kinetic character-

ization of several mutants in the active region and crystal

structure analysis of the enzyme, the structurally unique 310-

helix has been envisaged for the unusual low activity. Con-

sidering the inhibitory action of quercetin, it has been

Table 3 continued

S. no. Compound ID Residue Interaction

energy

(kcal mol-1)a

Interaction

dist. (A)

H-bond

energy

(kcal mol-1)b

MolDock

scorecRerank

scored

10 44258703

O

O

O

O

O

OO

H

H

H

H

H

H

H

H

HH

H

HArg286 -2.5 2.65 -15.8 -74.47 -64.94

Arg286 -1.65 3.1

Arg286 -0.17 3.1

Tyr311 -1.99 3.2

Ser177 -0.77 2.52

Glu233 -2.5 2.9

Glu101 -2.5 3.1

Asn302 -0.81 2.98

His96 -1.34 2.83

Glu101 -2.49 2.62

Ile304 -0.33 2.34

a The total interaction energy between the pose and the proteinb Hydrogen bonding energyc MolDock score is derived from the PLP scoring functions with a new hydrogen bonding term and new charge schemes (Thomsen and

Christensen, 2006)d The rerank score is a linear combination of E-inter (steric, van der Waals, hydrogen bonding, electrostatic) between the ligand and the protein,

and E-intra (torsion, sp2–sp2, hydrogen bonding, van der Waals, electrostatic) of the ligand weighted by pre-defined coefficients. (Thomsen and

Christensen, 2006)

Med Chem Res

123

Fig. 1 a Predicted bonded interactions (green dashed lines) between

CID 9818879 (green) and His96, Glu101, Arg286, Ile304, Gly306,

Ser307 and Tyr311 residues of HpDdl enzyme and b predicted non-

bonded electrostatic interaction between CID 9818879 and the

residues at the active site. c Binding mode of CID 9818879 (green)

to HpDdl (Color figure online)

Fig. 2 a Predicted bonded interactions (green dashed lines) between

CID6477685 (green) and Glu13, Glu101, Ser177, Glu233, Arg286,

Ile304 and Tyr311 residues of HpDdl enzyme and b predicted non-

bonded electrostatic interaction between CID6477685 and the resi-

dues at the active site. c Binding mode of CID6477685 (green) to

HpDdl (Color figure online)

Med Chem Res

123

Fig. 3 a Predicted bonded interactions (green dashed lines) between

CID 21633676 (green) and His96, Glu101 Ser177, Asn302, Ile304,

Gly306 and Tyr311 residues of HpDdl enzyme and b predicted non-

bonded electrostatic interaction between CID 21633676 and the

residues at the active site. c Binding mode of CID 21633676 (green)

to HpDdl (Color figure online)

Fig. 4 a Predicted bonded interactions (green dashed lines) between

quercetin (green) and His96, Glu101, Arg286, Asn302 and Ile304

residues of HpDdl enzyme and b predicted non-bonded electrostatic

interaction between quercetin and the residues at the active site.

c Binding mode of quercetin (green) to HpDdl (Color figure online)

Med Chem Res

123

reported that quercetin is a reversible inhibitor that is com-

petitive with the substrate ATP of Hpdl (Wu et al., 2008a).

Using D-cycloserine (DCS) as a positive inhibitor, the

inhibitor binding constant, Ki of ATP has been calculated (by

double reciprocal and secondary plots) to be 4.3 lM, while

IC50 of quercetin has been found to be 48.5 ± 4.3 lM.

Furthermore, surface plasmon resonance biosensor tech-

nology has been suitably used to determine the in vitro

binding affinity, KD (12.9 lM) of quercetin to HpDdl. The

afore-stated reports highlight the mode of binding of quer-

cetin to HpDdl to be competitive with respect to ATP. Thus,

we have restricted our present docking study under the pre-

text of available experimental data on the competitive mode

of inhibition of HpDdl by quercetin. The authors would,

however, like to mention at this juncture that the molecular

docking simulation work on the competitive inhibition of

ATP by quercetin and apigenin is under progress and shall be

reported in the subsequent communication.

Table 4 represents the Lipinski rule of five parameters

for the top docking hits and all the compounds used in our

study does not violate the rule of five to be an orally active

compound. Lipinski et al. (1997, 2000) described ‘rule of

five’ which impose limitation on the logP (the logarithm of

octanol/water partition coefficient), molecular weight and

the number of hydrogen bond acceptors and donors. The

rule states that most ‘drug-like’ molecules have logP \ 5,

molecular weight \500, number of hydrogen bond accep-

tors \10 and number of hydrogen bond donors \5. Mol-

ecules violating more than one of these rules may have

problems with bioavailability. From Table 4, it is also

observed that the hydrogen bond acceptors of the

CID9818879, CID6477685, CID21633676, CID25202270,

CID6477683, CID25202413 and CID10636768 are more

than that of quercetin ranging from 5 to 8 hydrogen bond

acceptors which could be an important factor because of

the hydrophobic nature of these compounds and hence

showing better affinity and interaction with HpDdl enzyme

as compared to quercetin. Moreover, it is also observed that

these seven compounds have lower topological surface

area (TPSA) values than quercetin suggesting that these

compounds have better oral bioavailability than quercetin

(the oral bioavailability is inversely proportional to topo-

logical polar surface area) (Freitas, 2006).

More specific analysis of pharmacological parameters

was inspected from ADME–Tox evaluation which is shown

in Table 5. Table 5 depicts some specific parameters related

to absorption, distribution, metabolism, excretion and tox-

icity for the top ten docking hits. In general, all compounds

presented advantages and disadvantages when compared to

each other. However, CID6477683 showed better bioavail-

ability (\70) as compared to quercetin and other compounds.

This compound could be a lead molecule.

We have also carried out a comparative analysis on

LD50 mouse and the probability of health effects which is

shown in Figs. 5 and 6. From Fig. 5, it is observed that

LD50 mouse (oral) of CID9818879, CID44258703,

CID10636768 are higher as compared to quercetin, while

CID6477685, CID21633676, CID25202270, CID6477683,

CID25202413, CID10636768, CID44258703 showed more

or less similar behaviour of LD50 mouse (intraperitoneal,

oral, intravenous, subcutaneous) with quercetin. Further-

more, the comparative analysis on health effects from

Fig. 6 reveals CID10359384 chances of health effect on

blood, gastrointestinal system and lung, CID6477685

chances of health effect on blood, cardiovascular and

kidney and CID6477683 chances of health effect on blood,

cardiovascular and liver. Interestingly, CID44258703,

CID25202413, CID10636768, CID9818879, CID25202270

and CID21633676 show better health effects in compari-

sons to quercetin.

These compounds which showed better health effect

could be a lead molecule or a novel class with enhanced

pharmacological properties. In addition, the analogues

showed higher absorption rate in comparison to quercetin

but with similar distribution rate with quercetin which is

shown in Table 5.

Conclusion

The present molecular docking simulation studies on the

analogues of quercetin (forming favourable interaction

with the active site residues) vouched for their inhibitory

action against HpDdl. A total of seven analogues of quer-

cetin showed favourable interaction better than quercetin,

exhibiting common molecular interaction with Glu101,

Ile304, Tyr311 residues of HpDdl. Furthermore, the com-

pounds used in this study do not violate the Lipinski rule of

five to qualify as orally active drugs. These analogues have

lower TPSA values than quercetin suggesting that the

former compounds have better oral bioavailability than the

Table 4 Lipinski rule of five filter including TPSA for the top poses

used in our study

S. no. Compound ID HBA HBD Mol wt xlogP3 Rot B TPSA

1 9818879 7 4 330.29 1.6 4 116

2 6477685 6 4 312.27 2 2 107

3 21633676 7 4 316.26 1.9 2 116

4 25202270 7 3 315.25 3.1 2 119

5 6477683 5 3 296.27 3.3 2 87

6 25202413 7 3 315.25 3.1 2 119

7 10636768 5 3 284.26 3.2 2 87

8 5280343 (quercetin) 1 5 302.23 1.5 1 127

9 10359384 8 5 332.26 1.5 2 137

10 44258703 7 4 316.26 1.9 2 116

Med Chem Res

123

Ta

ble

5A

DM

E–

To

xp

red

icti

on

par

amet

ers

for

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top

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ses

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(mg

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0.7

60

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60

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50

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80

.03

50

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.11

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40

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gD

bp

H1

.7(s

tom

ach

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.55

2.4

71

.87

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53

.12

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gD

bp

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gD

bp

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eju

nu

m,

ileu

m)

1.5

42

.46

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bp

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loo

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(cm

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(mg

kg

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(mg

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(mg

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(mg

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Med Chem Res

123

latter. Moreover, the ADME–Tox evaluation reveals one of

the analogue (CID64776834) to have better bioavailabil-

ity (\70) than the rest of the docked compounds used

in the study. In addition, CID44258703, CID25202413,

CID10636768, CID 9818879, CID25202270 and

CID21633676 showed better health effects and higher

absorption rate in comparisons to quercetin. These could be

possibly exploited as lead molecules or a novel class with

enhanced pharmacological properties. Though experimen-

tal studies are required to mark it as a lead compound for

the development of novel inhibitor, we conclude that

molecular docking studies of quercetin and its analogues at

active site residue of DdL enzyme of Hp would aid and

support in experimental testing of the compound as quer-

cetin is limited by its low oral bioavailability and low MIC.

Acknowledgments The authors thank Department of Biotechnol-

ogy (DBT), Government of India for providing Bioinformatics

Infrastructure Facility and Vice-Chancellor, Tezpur University for

support in carrying out this research work. Rocktotpal Konwarh also

acknowledges the receipt of his Senior Research Fellowship from

DBT, New Delhi.

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